Runlin Cai_Final Blog

ISSUE: Analysis of Factors Influencing Travel Mode Choice in LA County

Runlin Cai, CAUPD Affiliate

Background

According to the regional travel survey, transit mode share in LA county was 3% in 2000 (Source: SCAG Year 2000 Post-Census Regional Travel Survey Report). There are numerous factors influencing travel mode choice, including socioeconomic, urban form, transport system, policy, etc. My work is focusing on urban form and transport supply, especially different effect between transit and roadway.

Layout1: Range and Unit

The analysis is focusing on the range of whole Los Angeles County, aiming to see what factors influencing the travel mode choice especially transit using. And the analysis is mainly based on the data of census tract units.

Layout2: Urban Population Density

The overall population of Los Angeles County exceeds 9,800,000, and the mean population density is about 2,400 persons per square miles.

Layout3: High Density Areas

Although mean density is low, there are several parts with relatively high population density, including downtown and its southern area, and areas along some corridors such as Wilshire, Santa Monica and freeways.

Layout4: Transit Network

Transit Network of LA County is composed of 5 urban rail lines and bus transit lines which are mainly operated by Metro. The bus lines are divided into 3 types including rapid lines, local lines and community circle lines. Every type has its own operation speed and interval. For example, rapid lines usually have larger station spacing and thus higher speed.

Layout5: Population Coverage of Transit Network

According to buffer analysis of transit lines, it can be calculated that 5.2 million people, e.g. 53 percent of population, are covered in 0.5 mile buffer areas of transit lines.

Layout6: Urban Rail Network and Population Coverage

Urban rail network mainly covers LA downtown and its southern area. According to the buffer analysis of rail stations, there are just 74,000 people, e.g. 7 percent of whole population live around 0.5 mile to rail stations.

Layout7: Roadway Network and Population Coverage

Freeways and major arterials cover almost everywhere across the county range. And 4.7 million people, e.g. 48 percent of whole population live within 1 mile distance to freeway.

Layout8: Vehicles Used in Commuting

From the map we can see that LA County has a high car ownership rate and high using in commuting, while relatively low near rail station areas.

Layout9: Travel Demand Distribution

The left map represents that most travel time average in census tracts exceeds 20 minutes, which is determined by the sprawling pattern. And in the right map trip_to_work density for every unit is very high, especially along the main corridors.

Layout10: Trip_to_Work Driving Choice

The proportions of driving to work in most areas are beyond 70 percent which is contributed by developed freeway infrastructure. And we also find that the farther travel distance is , the more likely travelers choose to drive due to the travel time cost.

Layout11: Trip_to_Work Transit Choice

The transit shares in trip-to-work in most areas are lower than5 percent, but those areas near rail stations have a higher transit using.

Layout12: Mode Share around Rail Stations

Take urban rail network for analysis alone and find overall daily ridership up to 266,000 and transit mode share is almost 4 times as much as other areas. It means rail lines attract travelers for its punctuality and free-of-congestion.

Layout13: Urban Rail Effect

According to survey data, average boardings of rail stations exceeds 3,500, and average transit share in nearby census tracts is beyond 13%.

Layout14: Time Contour Map for Transit and Roadway

Comparing the effect of transit and roadway respectively, we can see why people prefer driving rather than taking transit. In the same time period, travelers would reach 2 times wide range as by driving as by transit. Within 1 hour’s driving from downtown center people can reach most of main attractions, while needing 2 hours by transit mode. The comparison clearly shows that the low-speed and insufficiency of transit system leads to the travelers’ high dependence on private car driving.

Conclusion

(1) Longer travel due to low density sprawling makes people prefer driving.

(2) Low level and insufficient transit network makes people unwilling to travel by transit.

(3) Urban rail transit would be better solution to attract travelers to take transit, and thus protecting environment and alleviating congestion.